3 answers

If you generate a c5 rule set nugget rather than a c5 decision tree nugget (or generate the rule set from the decision tree nugget) then you can generate a Rule Trace (SuperNode) from the c5 rule set nugget.

Its surfaced differently to the CHAID option but hopefully should address what you want.

The C5.0 algorithm is a proprietary algorithm owned by RuleQuest Research and is included in SPSS Modeler Professional and SPSS Modeler Premium. Because it is proprietary, we (IBM) has less control over what features are available and this is why you find some differences between the C5.0 and the other decision tree algorithms.

There is no good way (that I know of) to get the rule identifier for each record when using the C5.0 model as a decision tree. One option would be to train the model and then retrieve the entire tree from the XML content model of the model applier node and then recreate the decision tree on the canvas using a series of 'Derive' nodes. You can then use this to score the records adding in any additional information that you need. This is essentially what the "Rules Trace" does for a rule set.

While I understand the inclination to have this information, you should also consider what you will do with the rule identifier once you have: What kind of action will this additional information drive? This may help you determine if it is worth the additional effort.